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Scanning DMA Data Analysis I. Classification Transfer Function

Mai, Huajun and Flagan, Richard C. (2018) Scanning DMA Data Analysis I. Classification Transfer Function. Aerosol Science and Technology, 52 (12). pp. 1382-1399. ISSN 0278-6826. http://resolver.caltech.edu/CaltechAUTHORS:20181204-084110186

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Abstract

The scanning electrical mobility spectrometer (SEMS; also known as the scanning mobility particle sizer, SMPS) enables rapid particle size distribution measurements with a differential mobility analyzer (DMA)/condensation particle counter (CPC) combination by ramping the classifier voltage, and continuously counting particles into time bins throughout the scan. Inversion of scanning measurements poses a challenge due to the finite time response of the CPC; the distorted data can be deconvoluted to improve the fidelity of size distributions obtained with the SEMS/SMPS. Idealized models of the classification region have shown that, for rapid voltage scans that approach the particle residence time in the DMA, the nondiffusive transfer function deviates from the symmetric one seen at constant voltage. Nonetheless, most SEMS/SMPS data analyses employ the constant voltage transfer function, a result that is valid only for plug flow in the classification region. This article develops the scanning-mode transfer function for the actual geometry of the TSI Model 3081 DMA. Finite element calculations are used to determine the flow and electric fields through the entire DMA. The instantaneous scanning-DMA transfer function for diffusive particles is determined using Brownian dynamics simulations. Comparisons of the results from this simulation of a real instrument to those from the idealized models reveal the shortcomings of prior models in describing the instantaneous scanning-DMA transfer function. A companion paper (Part II) combines this scanning-mode transfer function with response functions for the other components of a SEMS/SMPS measurement system in order to derive the response function for the integrated measurement system.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1080/02786826.2018.1528005DOIArticle
ORCID:
AuthorORCID
Mai, Huajun0000-0002-0616-1986
Flagan, Richard C.0000-0001-5690-770X
Additional Information:© 2018 American Association for Aerosol Research. Received 30 Mar 2018, Accepted 24 Aug 2018, Accepted author version posted online: 04 Oct 2018, Published online: 20 Nov 2018. The authors thank Dr. K. Beau Farmer of TSI Inc. for providing detailed design drawings of the TSI Model 3081A DMA that made it possible to simulate flows, fields, and particle trajectories in the real instrument. We thank Yuanlong Huang, Wilton Mui, Amanda Grantz, Johannes Leppä, Paula Popescu, and John Seinfeld for useful discussions. This work was supported by the National Science Foundation under Grant No. AGS-1602086.
Funders:
Funding AgencyGrant Number
NSFAGS-1602086
Record Number:CaltechAUTHORS:20181204-084110186
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20181204-084110186
Official Citation:Huajun Mai & Richard C. Flagan (2018) Scanning DMA Data Analysis I. Classification Transfer Function, Aerosol Science and Technology, 52:12, 1382-1399, DOI: 10.1080/02786826.2018.1528005
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:91421
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:04 Dec 2018 19:17
Last Modified:21 Dec 2018 15:59

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